CN107208148B - Method and kit for the pathological grading of breast tumors - Google Patents

Abstract

The present disclosure is a method for identifying a tumor type in a breast tissue of a subject. The method comprises the following steps: performing one or more nucleic acid-based assays for identifying the presence of a mutation in breast tissue obtained from a subject in accordance with a first test module and a second test module, each test module being associated with the detection of at least one predetermined mutation in one or more genes, and each test module being configured to provide a positive result corresponding to the detection of the at least one predetermined mutation in the tissue or a negative result corresponding to the absence of a detectable predetermined mutation in the sample; and identifying a type of tumor of the breast tissue based on the provided results of the first and second testing modules. Preferably, the first test module is associated with detection of MED12 gene mutation and/or RARA gene mutation, while the second test module is associated with detection of FLNA gene mutation, SETD2 gene mutation and/or MLL2 gene mutation.

Description

Method and kit for the pathological grading of breast tumors

Technical Field

The present disclosure relates to methods that enable pathological stratification of breast tissue or identification of tumor type in a subject. More specifically, the methods of the present disclosure identify a tumor type, stage, or group by detecting or localizing mutations that are simultaneously present in breast tissue according to a predetermined test module associated with the mutation of interest. The present disclosure also provides kits configured to enable the methods of the present disclosure.

Background

Fibroepithelial tumors of the breast are characterized by two-phase proliferation of epithelial and stromal components. Fibroepithelial breast tumors include Fibroadenomas (FAs) and Phyllodes (PTs), the latter of which may be characterized histologically¹Further subdivided into benign, marginal and malignant grades. FAs affect millions of women worldwide each year³The frequency of PTs occurring is approximately1% or less of breast tumors, and up to 7% of Asian breast cancers⁴. PTs have a later median age of onset (35 years relative to 43 years), and a higher propensity for local recurrence than FAs, with distant metastasis also occurring in some malignant PTs⁵。

Previous studies have shown that PTs and FAs may be highly correlated⁴. FA-like regions are not uncommon in the histopathological examination of PTs, and several studies suggest clonal development from FA to PT^6-10. On a molecular level, frequent mutations of exon 2 of RNA polymerase II transcription mediator subunit 12(MED12) have recently been observed in FAs and PTs^2,11-14While gene expression and DNA methylation analysis have been implicated in the development of PT genes such as HOXB13 and HMGA2^15-17. Higher copy number alteration rates (CNA) are also associated with higher levels of PTs^18,19One recent study analyzed a small number of PTs (n 15, 5 per grade) using a targeted cancer genome, revealing that recurrent mutations in tumor protein p53(TP53) and single mutations in retinoblastoma protein (RB1) and neurofibromin 1(NF1) were only present in high-grade PTs¹¹. However, unlike Breast Cancers (BCs) whose comprehensive mutational patterns have been extensively studied^20-23Little is known about the genetic and molecular relationships linking different types of mammary fibroepithelial lesions.

Diagnosis and typing of PTs often presents a challenge to pathologists, particularly in distinguishing benign PT from FA. This typing is of clinical importance in providing disease-specific therapy to patients with FA, PT or BC.

Disclosure of Invention

The present disclosure is directed to a method for grading, identifying or classifying a breast tissue-associated tumor in a subject. By correctly identifying the type, stage, or group of tumors, the present disclosure facilitates disease-specific therapy for a subject.

It is another object of the present disclosure to use one or more nucleic acid-based assays to aid in the classification, identification or classification of tumor types associated with breast tissue of a subject. The methods of the present disclosure use nucleic acid-based assays that provide reliable results for use as a supportive diagnostic tool in addition to physical examination of samples for tumor grading. In particular, the methods of the present disclosure allow a pathologist to substantially distinguish benign PTs from FAs.

It is a further object of the present disclosure to provide a kit comprising, at least in part, the necessary reagents to facilitate performance of the above-described one or more nucleic acid-based assays in a desired tumor grade. The kits of the present disclosure can be operated in various embodiments, under different platforms for nucleic acid-based assays.

At least one of the foregoing objects is met, in whole or in part, by the present disclosure, wherein one of the embodiments of the present disclosure is a method for identifying a tumor type in a breast tissue of a subject, the method comprising the step of performing one or more nucleic acid-based assays to identify a mutation present in the breast tissue obtained from the subject by a first test module and a second test module, both of the first and second test modules being associated with the detection of at least one predetermined mutation in one or more genes and configured to provide a positive result corresponding to the detection of the at least one predetermined mutation in the tissue or a negative result corresponding to the absence of a detectable predetermined mutation in a sample, the first test module being associated with the detection of a mutation in the MED12 gene and/or a mutation in the Retinoic Acid Receptor Alpha (RARA) gene, the second test module being associated with a mutation in the filamin a alpha (FLNA) gene, detection of SET domain mutations containing the 2(SETD2) gene and/or mixed lineage leukemia protein 2(MLL2) gene mutations is correlated; and identifying a type of breast tissue tumor based on the results provided by the first and second testing modules. Preferably, the type of tumor is considered to be a fibroadenoma when the results of the first test module and the second test module are positive and negative, respectively. Alternatively, when the first test module and the second test module both result positive, the type of tumor is considered to be a phylloid tumor. In addition, the first test module can be further associated with detection of a telomerase reverse transcriptase (TERT) gene mutation in the subject.

According to various preferred embodiments, the step of performing one or more nucleic acid-based assays further comprises a third test module associated with detecting a mutation in the NF1 gene, a mutation in the RB1 gene, and/or a mutation in the phosphatidylinositol 4, 5-bisphosphate-3-kinase catalytic subunit alpha (PIK3CA) gene. Preferably, the type of tumor is considered a malignant phylloid tumor when the results of the first test module, the second test module, and the third test module are all positive.

According to various preferred embodiments of the methods of the present disclosure, the mutation of the MED12 gene is a splice site mutation located at position-8 of exon 2 of the MED12 gene, a missense mutation located at codon 44 of the MED12 gene cDNA or a missense mutation located at codon 36 of the MED12 gene cDNA.

According to a more preferred embodiment, the mutation in the RARA gene corresponds to or results in p.f286del, p.f287l, p.n299h, p.r394q, p.l409del and/or p.g289r found in translation of the RARA gene from the subject.

For various examples, mutations in the FLNA gene correspond to p.a1191t, p.s1199l, p.p1244s, p.1687-1688TV > M, and/or p.s1186w found in polypeptides translated from the subject's FLNA gene. These mutations to be detected are in particular missense mutations on the resulting polypeptide.

For various examples, mutations in the SETD2 gene involved p.r1674-1675EA > D, p.k1587fs, p.q1545 x, p.y1605fs and/or p.f1651fs found in their translatable polypeptides. Mutations found in the SETD2 gene are often associated with missense or somatic mutations.

In many embodiments, the mutation to be detected in the TERT gene is preferably located in the promoter region. For example, mutations at-124 and/or-146 in the promoter region of the TERT gene result in missense mutations.

In another aspect of the present disclosure, a kit for identifying a tumor type in breast tissue of a subject is provided. Preferably, the kit comprises at least one platform capable of performing one or more nucleic acid-based assays to identify the presence of a mutation in breast tissue obtained from a subject according to a first test module and a second test module, each test module associated with the detection of at least one predetermined mutation in one or more genes, each test module configured to provide a positive result corresponding to the detection of at least one predetermined mutation in the tissue or a negative result corresponding to the absence of a detectable predetermined mutation in the sample, the first test module associated with the detection of MED12 gene mutation, TERT and/or RARA gene mutation, the second test module associated with the detection of FLNA gene mutation, SETD2 gene mutation and/or MLL2 gene mutation. Preferably, the test module is configured to emit a detectable or visible signal in response to any positive result. The type of tumor is considered to be a fibroadenoma when the results of the first test module and the second test module are positive and negative, respectively. Alternatively, when the first test module and the second test module both result positive, the type of tumor is considered to be a benign leaf tumor.

In one or more embodiments of the kits of the present disclosure, the at least one platform further comprises a third test module associated with detecting a NF1 gene mutation, an RB1 gene mutation, and/or a PIK3CA gene mutation. By including the third test module, the kits of the present disclosure can further consider, grade, or identify the tumor type as a malignant phylloplastic tumor when the results of the first test module, the second test module, and the third test module are all positive.

In some embodiments, the breast tissue is stromal cells for use with the kits for tumor staging or identification of the present disclosure.

Drawings

FIG. 1A is a combinatorial graph showing the distribution of frequent mutant genes in 100 fibroepithelial tumors identified by targeted sequencing, including 21 FAs and 79 PTs, the central graph showing the grouping of the frequent mutant genes, the dots indicating the occurrence of a second mutation in the same patient, the left histogram showing the number of mutations and adjacent numbers to indicate the frequency of the mutations in the group, the right column showing the frequency of subtype mutations, and the asterisks indicating that the samples did not match normally;

FIG. 1B is a simple chart illustrating an overview of key genetic variations and pathways associated with each stage of the fibroepithelial tumor profile based on the findings of the present disclosure;

FIG. 2A is a schematic representation of mutations in MED12, the frequency of each of which is indicated in parentheses after its left to right labeling as MED, transcription mediating complex subunit Med12, MED12-LCEWAV, eukaryotic mediating 12 sub-domain, MED12-PQL, eukaryotic mesoplasmic 12 chain protein binding domain;

figure 2B is a schematic of RARA mutations, domains in RARA: NR _ DBD (DNA binding domain of retinoic acid receptor); NR _ LBD (ligand binding domain of retinoic acid receptor);

fig. 2C is a schematic of FLNA mutations, domains in FLNA: CH (calmodulin homeodomain) and IG _ FLMN (filamin-type immunoglobulin domain);

fig. 2D is a schematic of the SETD2 mutation, domain in SETD 2: AWS (associated with the SET domain), SET (Su (var)3-9, enhancer of zeste, trithorax) domain, WW (WWP domain) and SRI (SET2Rbp1 interaction domain);

fig. 2E is a schematic of the MLL2 mutation, domain in MLL 2: zf-HC (PHD-like zinc binding domain), finger ring (truly interesting new gene) domain, PHD (PHD zinc finger), HMG (high mobility group-box domain) FYRN (F/Y rich N-terminus), FYRC (FY domain rich C-terminal region) SET (su (var)3-9, enhancer of zeste, trithiomax) domain;

FIG. 3 summarizes the somatic mutation map of the phyllodes tumor, and (A) shows the number of somatic mutations in FA and PT. P <0.001(B) shows the frequency of each mutation in 22 phyllodes, expressed as the number of mutations per megabase (Mb) covering the target sequence, (c) the mutation signature in 22 pairs of PTs, and (d) shows the number of variant copies of 50 target genes in 100 fibroepithelial tumors, with high grade tumors tending to have more CNAs compared to lower grade tumors. N.s., not significant p <0.05, p <0.01, p < 0.001;

figure 4A is a graph showing the percentage of samples with somatic mutations in fibroepithelial tumors and solid tumors from TCGA samples identified by published data obtained from cbioport (number of samples per study in parentheses), where ACC is adrenocortical carcinoma and ccRCC is renal clear cell carcinoma;

figure 4B is a graph showing the expression levels of RARA detected by qPCR in fibroepithelial tumors, with RARA-containing wild-type (17 cases) or mutant (13 cases);

figure 4C is a graph showing that RARA mutant transcriptional activity was lower than wild-type RARA, where HEK293 cells were transfected with the RARE cognal reporter and expression plasmids containing cDNA for empty vector, wild-type and mutant RARA, respectively, and transcriptional activity was measured in the absence and presence of RA stimulation (error line SD, n 3);

figure 4D is a graph showing the results of a mammalian two-hybrid assay performed in HEK293 cells to assess the interaction of wild-type or mutant RARA with the nuclear co-suppressor NCoR1 in the absence and presence of RA (error line SD, n 3);

FIG. 5A shows a schematic map of somatic FLNA mutations in breast cancer, determined using the domains of the FLNA protein, for variations in breast cancer according to published data obtained from cBioPortal (TCGA), where CH is the Calponin homology domain and IG-FLMN is the filamin-type immunoglobulin domain;

figure 5B shows the cDNA Sanger sequencing results of FLNA variants in 3 fresh frozen PTs;

FIG. 6A is a graph revealing the EGFR amplification pattern in borderline (sample 1056) and malignant (sample 1076) PT;

figure 6B is a representative graph of IHC staining of EGFR, showing protein levels and EGFR location in the border PT (sample 1056), the image showing that EGFR protein is localized only in stromal cells and not present in epithelial cells;

FIG. 7 shows a comparison of mutation profiles in FA, PT and BC based on targeted sequencing analysis, along with representative genes known to be significantly mutated in BCs (TP53, PIK3CA, MAP3K1, GATA3 and CDH 1);

fig. 8A is a photomicrograph of the hematoxylin and eosin (H & E) stained portion of sample 1007 obtained by Laser Capture Microdissection (LCM), where S denotes stroma and E denotes epithelium;

figure 8B shows Sanger sequencing of MED12, RARA, and BRCA1 in bulk tissue, epithelium, and stroma regions of the same stained sample provided in figure 8A, the sequencing results showing that the mutations are unique to the stroma regions;

figure 9(a) is a low magnification micrograph of a portion of a paraffinized tumor with broad leaf-like stromal leaf-like protrusions to crevice spaces lined by benign epithelium, (B) is medium magnification of mild to moderate cell stroma covered by benign double-layered epithelium, (C) is a micrograph showing the permeability boundaries of stromal cells penetrating into adjacent fat, (D) shows stromal mitotic activity by mitosis, (E) is Sanger sequencing of RB1 and EGFR of sample 004 tumor and matching blood;

figure 10A is a micrograph of H & E stained sections showing concurrence of FA and PT, selected for macro dissection from one patient, the acquisition of cancer-associated genes in the mutation mapped only in PT, the lowest micrograph was IHC staining of EGFR, the protein of the PT region was prominent, but not in the FA-like region; and

fig. 10B depicts the somatic mutation profile based on the concurrent and longitudinal FAs/PT of the histological subtype of each patient reported in the above figure, the bottom panel being a schematic for indicating the type of mutation identified.

Detailed Description

The present invention may be embodied in other specific forms without departing from its structures, methods, or other essential characteristics as broadly described and claimed herein. The described embodiments are to be considered in all respects only as illustrative and not restrictive. The scope of the invention is, therefore, indicated by the appended claims rather than by the foregoing description. All changes which come within the meaning and range of equivalency of the claims are to be embraced within their scope.

As used herein, unless otherwise noted, the terms "comprise" and "comprise," and grammatical variations thereof, are intended to mean "open" or "inclusive" language such that they include the recited elements but also permit inclusion of additional, unrecited elements.

As used herein, the phrase "in an embodiment" refers to in some embodiments, but not necessarily all embodiments.

As used herein, the term "about" or "approximately" in the context of component concentrations, conditions, other measured values, and the like, refers to +/-5% of the stated value, or +/-4% of the stated value, or +/-3% of the stated value, or +/-2% of the stated value, or +/-1% of the stated value, or +/-0.5% of the stated value, or +/-0% of the stated value.

The term "polynucleotide" or "nucleic acid" as used herein refers to mRNA, RNA, cRNA, cDNA or DNA. The term generally refers to oligonucleotides greater than 30 nucleotide residues in length.

The term "primer" as used herein refers to an oligonucleotide capable of priming the synthesis of a primer extension product in the presence of a suitable polymerizing agent when paired with a DNA strand. For maximum efficiency of amplification, the primer is preferably single-stranded, but may also be double-stranded. The primer must be long enough to prime the synthesis of extension products in the presence of the polymerization agent. A primer may be "substantially complementary" to a sequence on the template to which it is designed to hybridize and serve as a site for initiation of synthesis. By "substantially complementary" is meant that the primers are sufficiently complementary to hybridize to the target polynucleotide. Preferably, the primer does not contain a mismatch to the template to which it is designed to hybridize, but this is not required. For example, non-complementary nucleotide residues may be attached to the 5' end of the primer, with the remainder of the primer sequence being complementary to the template. Alternatively, a non-complementary nucleotide residue or a stretch of non-complementary nucleotide residues may be interspersed into the primer, so long as the primer sequence has sufficient complementarity with the template sequence to hybridize therewith, thereby forming a template for synthesis of a primer extension product.

The term "gene" as used herein may refer to a DNA sequence having a functional meaning. It may be a natural nucleic acid sequence, or a recombinant nucleic acid sequence derived from a natural source or a synthetic construct. The term "gene" may also be used to refer to, for example, without limitation, cDNA and/or mRNA encoded directly or indirectly by or derived from a genomic DNA sequence.

In one broad aspect of the present disclosure, a method for identifying a tumor type in breast tissue of a subject is disclosed. Preferably, the method of the present disclosure comprises the steps of: performing one or more nucleic acid-based assays to identify the presence of a mutation in breast tissue obtained from a subject according to a first test module and a second test module, each test module associated with detection of at least one predetermined mutation in one or more genes, each test module configured to provide a positive result corresponding to detection of at least one predetermined mutation in the tissue or a negative result corresponding to absence of a detectable predetermined mutation in the sample, the first test module associated with detection of MED12 gene mutation, TERT-based mutation, and/or RARA gene mutation, the second test module associated with detection of FLNA gene mutation, SETD2 gene mutation, and/or MLL2 gene mutation. And determining the type of tumor of the breast tissue based on the results provided by the first and second testing modules.

It will be understood by one of ordinary skill that the at least partially nucleic acid-based assays described herein may also include at least some well-known methods or steps for performing the assays, although they may not be fully described in detail in this specification. For example, a portion of a nucleic acid-based assay may involve the step of extracting or isolating deoxyribonucleic acid (DNA) and/or ribonucleic acid (RNA) material containing genetic information about a subject or subject tissue sample using any method or commercial kit. As in some preferred embodiments, a portion of the nucleic acid-based assay may also involve performing a Polymerase Chain Reaction (PCR) on the isolated DNA or RNA material, along with predetermined thermal cycling and conditions to amplify the gene or portions of the gene, for analysis in a test module to complete the pathological staging. These pretreatments or processes may form part of a nucleic acid-based assay, ultimately leading to the identification of alleles, mutations and/or genotypes of the desired genes for tumor grading and classification.

According to some preferred embodiments of the methods of the present disclosure, the nucleic acid-based assay preferably identifies, detects and/or genotyping potential mutations present in one or more genes in a subject that has contributed to tumor or cancer development. The nucleic acid-based assays of the present disclosure include sequencing a gene of interest. Sequencing may be performed on polynucleotides amplified and/or replicated from DNA or RNA material isolated from breast tissue. More specifically, the sequencing methods employed in the present disclosure for enabling mutation identification or detection can be Sanger sequencing and/or label amplification ultra-deep sequencing, which is efficient and capable of highly accurate and reliable derivation of the identified mutations of interest disposed in the test module. Details of Sanger sequencing and/or label amplification ultra-deep sequencing are further set forth in the examples incorporated below. It is important to other skilled artisans to appreciate that other known equivalent sequencing or non-equivalent procedures or methods can be used to detect the presence of a mutation of interest in the analyzed polynucleotide to carry out the methods of the present disclosure, and such modifications should not depart from the scope of the present disclosure. Other known methods that can be used to identify or assist in identifying these mutations can be, but are not limited to, temperature gradient gel electrophoresis, capillary electrophoresis, amplification-hindered mutant system polymerase chain reaction (ARMS-PCR), dynamic allele-specific hybridization (DASH), target capture for Next Generation Sequencing (NGS), high density oligonucleotide SNP arrays, or Restriction Fragment Length Polymorphism (RFLP). The present disclosure utilizes patterns, outcomes, or results from test modules to grade the tumor stage or type of tissue sample with respect to predetermined genes associated with a given module, rather than just employing specific primers or a single platform to achieve the grading or classification. Modifications to primers or platforms that can perform the tumor grading methods of the invention, such as differences in sequencing primer length or hybridization position, are within the scope of the disclosure.

As described above, the first test module and the second test module are each associated with the detection of at least one mutation in one or more genes to which the test module is specifically related and provide results suitable for subsequent tumor stage staging or tissue sample type. More specifically, in preferred embodiments, the first test module is associated with the detection of a mutation in the MED12 gene, TERT gene, and/or RARA gene. More preferably, the first module is associated with the detection of more than one mutation associated with the MED12 gene, TERT gene, and/or RARA gene. For example, the mutation detectable by the MED12 gene and associated with the first test module can be any one of a splice site mutation located at exon 2-8 of the MED12 gene, a missense mutation located at cDNA codon 44 of the MED12 gene, or a missense mutation located at cDNA codon 36 of the MED12 gene. Similarly, a detectable mutation of the RARA gene associated with the first test module may be any one of the p.f286del, p.f287l, p.n299h, p.r394q, p.l409del and/or p.g289r mutations that result in missense mutations in the polypeptide that is translated thereof. Furthermore, the mutation to be detected in the TERT gene is preferably located in the promoter region. For example, mutations at-124 and/or-146 in the promoter region of the TERT gene result in missense mutations.

According to many embodiments of the disclosed methods, the second test module is preferably associated with a detectable predetermined mutant located in the FLNA gene, the SETD2 gene, and/or the MLL2 gene. More specifically, the mutation or mutations detected in the FLNA gene associated with the second test module typically produce p.a1191t, p.s1199l, p.p1244s, p.1687-1688TV > M, and/or p.s1186w in the polypeptide translated therefrom. The mutations associated with the SETD2 gene and associated with the second test module were any single or combined mutation producing top.r1674-1675EA > D, p.k1587fs, p.q1545 x, p.y1605fs and/or p.f1651fs, translatable from SETD 2. Similarly, the mutation of the MLL2 gene to be detected and associated with the second test module is typically any mutation that causes an inactivating mutation, such as p.v5482fs, p.q1139 x, p.g2668fs, p.q3814 x and/or p.l3457fs found in the polypeptide encoded by the MLL2 gene. For a few preferred embodiments, the second test module of the methods of the present disclosure may be further associated with mutations of other genes in addition to the FLNA gene, the SETD2 gene, and/or the MLL2 gene.

These additional genes with mutations of interest, which may be inferred or indicative of breast tumor type or stage, may be associated with a second test module, a BCL-6 co-suppressor protein (BCOR) gene and a mitogen-activated protein kinase 1(MAP3K1) gene.

In some embodiments of the methods of the present disclosure, the second testing module may be configured to detect the presence of a genetic mutation in a subject other than the FLNA gene, the SETD2 gene, and/or the MLL2 gene. For example, the second test module may be arranged to discover inactivating mutations in the B-cell lymphoma factor 6 co-suppressor (BCOR) gene, such as p.k460, p.w534 and/or p.k175fs, or somatic mutations, such as p.m312fs and/or p.q409fs, in the mitogen-activated protein kinase 1(MAP3K1) gene of the subject.

To better stratify or identify the tumor stage of a breast tissue sample, performing one or more nucleic acid-based assays may further include a third test module associated with detecting NF1 gene mutations, RB1 gene mutations, and/or PIK3CA gene mutations. With the aid of the third testing module, the method of the present disclosure can further grade or identify those tissue samples of the leaf-like tumor that have entered the borderline malignancy or malignant stage. Preferably, the mutation of the NF1 gene associated with the third test module is a mutation found in its translatable polypeptide with respect to p.k1014, p.r416 and/or p.d 2283fs. These mutations in the third test module targeting the NF1 gene caused either nonsense or frameshift mutations, resulting in tumorigenesis. Similarly, the mutation of the RB1 gene associated with the third test module is a mutation found in its translatable polypeptide with respect to p.q504 x, p.n316fs and/or p.p 796fs. Mutations in these RB1 genes also cause nonsense or frameshift mutations. For the PIK3CA gene, the mutation of interest associated with the third test module was mainly related to p.h1047r/L, which is a missense mutation.

In addition to mutations in the NF1 gene, RB1 gene, and/or PIK3CA gene, other embodiments of the methods of the present disclosure may have more mutations in other associated genes found by the third test module. As more mutation sites are covered, the methods of the present disclosure can provide greater accuracy in detecting, diagnosing, classifying, grouping, or identifying various stages of tumor development in a subject in time. The third test module can be used to detect frequent mutations associated with p.l62r in polypeptides encoded by the Epidermal Growth Factor Receptor (EGFR) gene, p.i 33del-related non-frameshift deletion mutations found in polypeptides encoded by the phosphatase tensin homolog (PTEN) gene, p.294fs or p.c229fs-related inactivating frameshift mutations found in polypeptides encoded by the tumor protein P53(TP53) gene, p.w407r-related somatic mutations found in polypeptides encoded by the Erb-B2 receptor tyrosine kinase 4(ERBB4) gene, and/or replication of the insulin-like growth factor 1 receptor (IGF1R) gene of the subject.

According to a preferred embodiment, said first, second and/or third module is made to produce a positive result as soon as at least one predetermined mutation of the gene associated with a particular test module is detected, and vice versa. For example, the first test module produces a positive result in response to at least one mutation detected in the MED12 gene, TERT gene, and/or RARA gene of breast tissue of the subject. In contrast, the first test module produces a negative result in the absence of any detectable predetermined mutation associated with the MED12 gene, TERT gene, and/or RARA gene. Similar principles apply to the second and third test modules to implement the methods of the present disclosure in tumor grade identification. In many preferred embodiments, each mutation of a gene under consideration in a test module can be detected or identified by performing a separate nucleic acid-based assay under different known principles or platforms. For these embodiments, nucleic acid-based assays of individual mutations of the genes involved may not be performed in parallel, but rather the results produced by each assay are retrieved or collected into an associated test module to calculate or produce their results. According to other preferred embodiments, the methods of the present disclosure may run similar tests simultaneously to detect mutations or alleles of genes respectively associated with different modules in a single run of the same platform, correlating the results of each analyzed mutation with a predetermined module for calculating the results of subsequent tumor grading. From the foregoing, the nucleic acid-based assays described herein are not limited to a single operating platform or mechanism, although for cost and/or time savings, it is preferred to identify mutations of interest of the relevant gene by one platform.

As set forth in the foregoing description, the methods of the present disclosure effectively rank the type of tumor in response to results calculated, generated, or emitted by the test module used. According to various preferred embodiments, the method of the present disclosure considers the tumor type of the breast tissue sample to be fibroadenoma when the results of the first test module and the second test module are positive and negative, respectively. The inventors of the present disclosure found that biomarkers associated with early onset of FA can be associated with detectable mutations in MED12, TERT gene, and/or RARA gene in a subject. At the same time, the FA sample typically does not contain any detectable mutations in those genes associated with the second test module, e.g., FLNA, SETD2, MLL2, BCOR, MAP3K 1. Similarly, in addition to the positive and negative results of the first and second test modules, respectively, when the third module delivered a negative result, the present disclosure also correlated the analyzed breast tissue as FA, indicating that no significant mutations of interest could be detected in these genes associated with the third module.

According to a preferred embodiment, when the results of both the first test module and the second test module are positive, the method of the present disclosure may treat the type of tumor as a leaf tumor. Based on the tests and experiments performed, the present disclosure recognizes that the development of leaf tumors appears to have mutations in genes associated with both the first and second test modules. In particular, in addition to identifying a mutation of interest in a gene associated with the first test module, a tumor type of a breast tissue sample that conforms to a deliberate mutation in the FLNA, SETD2, MLL2, BCOR or MAP3K1 genes may conveniently be considered a leaf tumor.

To further differentiate or grade the identified phyllodes, in some preferred embodiments, the present disclosure elicits a third test module in addition to those present in the first and second modules to detect mutations in additional genes of the subject. In particular, when the results of the first, second and third test modules are all positive, the obtained tumor type of the breast tissue is considered to be a malignant phyllode tumor, meaning that the obtained sample carries at least one mutated gene in each test module. A sample or test subject with a positive test module result may also have two or more mutations in one or more genes associated with the particular test module. On the other hand, when the result of the third test module is negative and the results of the first and second test modules are positive, the method of the present disclosure preferably treats the type of tumor of the breast tissue sample as a benign leaf tumor.

Another aspect of the present disclosure relates to a kit for identifying a tumor type in breast tissue of a subject. Preferably, the kit comprises at least one platform capable of performing one or more nucleic acid-based assays to identify the presence of a mutation in breast tissue obtained from a subject according to a first test module and a second test module, each of the first and second test modules being associated with the detection of at least one predetermined mutation in one or more genes and configured to provide a positive result corresponding to the detection of at least one predetermined mutation in the tissue or a negative result corresponding to the absence of a detectable predetermined mutation in the sample, the first test module being associated with the detection of MED12 gene mutation, TERT and/or RARA gene mutation, the second test module being associated with the detection of FLNA gene mutation, SETD2 gene mutation and/or MLL2 gene mutation.

At least one platform for identifying or assisting in identifying these mutations that may be useful with the kits of the present disclosure may be, but is not limited to, temperature gradient gel electrophoresis, capillary electrophoresis, amplification-hindered mutation system polymerase chain reaction (ARMS-PCR), dynamic allele-specific hybridization (DASH), target capture for Next Generation Sequencing (NGS), high density oligonucleotide SNP arrays, or Restriction Fragment Length Polymorphism (RFLP). According to various preferred embodiments of the kits of the present disclosure, each mutation of a gene under consideration in the test module may be subjected to a separate nucleic acid-based assay, which is performed in at least one of the above-described platforms, for detection or identification. In some embodiments, nucleic acid-based assays of individual mutations of the genes involved may not be performed in parallel, but rather the results produced by each assay are retrieved or collected into an associated test module to calculate or produce their results. In other preferred embodiments, the kits of the present disclosure can be used, at least in part, to run similar assays simultaneously to detect mutations or alleles of genes associated with different modules, respectively, in a single platform, and to correlate the results of each analyzed mutation with a predetermined module for calculating the results of subsequent tumor grading.

In a more preferred embodiment, the nucleic acid-based assay of the kits of the present disclosure comprises sequencing a gene of interest. Sequencing may be performed on polynucleotides amplified and/or replicated from DNA or RNA material isolated from breast tissue. More specifically, the sequencing methods employed in the present disclosure for enabling mutation identification or detection can be Sanger sequencing and/or label amplification ultra-deep sequencing, which is efficient and capable of highly accurate and reliable derivation of the identified mutations of interest disposed in the test module.

In accordance with the foregoing, the first and second test modules of the kits of the present disclosure are each associated with the detection of at least one mutation in one or more genes with which the test module is specifically associated and provide results suitable for subsequent tumor stage staging or tissue sample type. More specifically, in various preferred embodiments of the kits of the present disclosure, the first test module is associated with the detection of a mutation in the MED12 gene, TERT gene, and/or RARA gene. More preferably, the first module is associated with the detection of more than one mutation associated with the MED12 gene, TERT gene, and/or RARA gene. For example, the mutation detectable by the MED12 gene and associated with the first test module can be any one of a splice site mutation, such as a missense mutation located at exon 2-8 of the MED12 gene, a missense mutation located at cDNA codon 44 of the MED12 gene, or a missense mutation located at cDNA codon 36 of the MED12 gene. Similarly, the detectable mutation of the RARA gene associated with the first test module may be any one that results in p.f286del, p.f287l, p.n299h, p.r394q, p.l409del and/or p.g289r missense mutations in the polypeptide translated therefrom. For the TERT gene, the mutation to be detected is preferably located in the promoter region. For example, a mutation at-124 and/or-146 of the promoter region of the TERT gene that results in a missense mutation.

According to some preferred embodiments, the second test module is preferably associated with a detectable predetermined mutant located in the FLNA gene, the SETD2 gene and/or the MLL2 gene. More specifically, the one or more mutations detected in the FLNA gene associated with the second test module are mutations corresponding to p.a1191t, p.s1199l, p.p1244s, p.1687-1688TV > M, and/or p.s1186w in the polypeptide translated from the FLNA gene of the subject. The mutation associated with the SETD2 gene and associated with the second test module is any single or combined mutation found in the polypeptide from which it is derived that results in p.r1674-1675EA > D, p.k1587fs, p.q1545 x, p.y1605fs and/or p.f 1651fs. Similarly, the mutation of the MLL2 gene to be detected and associated with the second test module is typically any mutation that causes an inactivating mutation, such as p.v5482fs, p.q1139 x, p.g2668fs, p.q3814 x and/or p.l3457fs found in the polypeptide encoded by the MLL2 gene. For a few preferred embodiments, the second test module of the kits of the present disclosure may be further associated with mutations of other genes in addition to the FLNA gene, SETD2 gene, and/or MLL2 gene. These additional genes with mutations of interest, which may be inferred or indicative of breast tumor type or stage, may be associated with a second test module, a BCL-6 co-suppressor protein (BCOR) gene and a mitogen-activated protein kinase 1(MAP3K1) gene.

The kits of the present disclosure facilitate staging the tumor stage or type of a tissue sample based on predetermined and related genes using patterns, outcomes or results from a test module. Preferably, the type of tumor of the breast tissue sample is considered to be a fibroadenoma when the results of the first and second test modules are positive and negative, respectively. Conversely, when the results of the first test module and the second test module are both positive, the tumor type of the breast tissue being tested is considered to be a benign leaf tumor.

In more preferred embodiments, the kits of the present disclosure may further comprise a third test module associated with detecting NF1 gene mutations, RB1 gene mutations, and/or PIK3CA gene mutations. With the aid of the third testing module, the kit of the present disclosure facilitates further grading or identification of tumor types of those tissue samples of leaf tumors that have entered the borderline malignancy or malignant stage. Preferably, the mutation of the NF1 gene associated with the third test module is a mutation found in its translatable polypeptide with respect to p.k1014, p.r416 and/or p.d 2283fs. Similarly, the mutation of the RB1 gene associated with the third test module is a mutation found in its encoding polypeptide with respect to p.q504 x, p.n316fs and/or p.p 796fs. For the PIK3CA gene, the mutation of interest associated with the third test module typically involves a mutation that results in p.h1047r/L encoding the polypeptide. Thus, when the results of the first, second and third test modules are all positive, the tumor type of the obtained breast tissue is considered by the kit of the present disclosure to be a malignant leaf tumor, meaning that the obtained sample carries at least one mutated gene in each test module. On the other hand, when the result of the third test module is negative and the results of the first and second test modules are positive, the kit of the present disclosure preferably allows a user of the kit to consider the tumor type of the breast tissue sample as a benign leaf tumor.

To accelerate the generation of the results of the kits of the present disclosure, the test module is preferably configured to emit a detectable or visible signal corresponding to any positive result, and vice versa. Whenever one mutation of interest associated with a given module is identified, a machine or user readable signal will be generated to highlight the positive results obtained. For example, the kit of the present disclosure may take the form of a DNA chip on which a plurality of polynucleotides are anchored to readily hybridize to target gene segments, potentially binding to a mutation of interest amplified from a breast tissue sample. The test module may be a set of polynucleotides or a dedicated region on the chip. Discrete spots on the DNA chip belonging to a particular test module, attached to polynucleotides specifically designed to hybridize under stringent conditions only target gene fragments having a mutation of interest, produce a microarray machine-readable signal when successful hybridization occurs, to signal and correlate the detection of the mutation of interest to that particular test module to produce a positive result.

Based on the physical examination of breast biopsies, the above-described methods and/or kits may, in addition to routine tumor grading or classification, also be used for supportive diagnosis, whether or not further staining is performed. If there is a discrepancy between the results of the histological examination and the methods and/or kits of the present disclosure, the physician may have to review the tissue sample. For example, samples that are considered FA or benign PT, for which all three test modules give positive results, should be reviewed by a physician. It is clearly shown in the experiments of the present disclosure that FA or benign PT samples should be free of any mutations present in the genes associated with the third module of the methods and/or kits of the present disclosure. The results of physical or histological examination are most likely false negatives. The health condition of the subject may be compromised due to delayed treatment as a result of misdiagnosis. The methods and/or kits of the present disclosure provide additional mechanisms to prevent false negative or false positive results from subjective histological examinations that rely primarily on the experience of the performing physician.

The following examples are intended to further illustrate the present invention and are not intended to limit the invention to the specific embodiments described herein.

Example 1

Fibroepithelial tumors were diagnosed and typed based on clinical features and histopathological examination of surgically excised tumors. All cases were examined histologically by at least 2 breast pathology specialists. Diagnostic and grading criteria recommendation for classification of breast tumors based on the world health organization¹. Briefly, a phylloid tumor is diagnosed when a fibroepithelial tumor exhibits an exaggerated, intratubular pattern with a stromal hypercellular frond-like body. Benign leaf tumors are diagnosed when the lesion exhibits mild stromal cellularity, minimal nuclear heterogeneity, border progression, 4 or fewer mitoses per 10 high power fields, and no stromal overgrowth. Malignant phyllo-tumors can be diagnosed when there is significant stromal cellularity and atypia, stromal overgrowth and penetrating margins, and mitotic activity of 10 or more per 10 high power fields. Tumors with intermediate characteristics are considered borderline. All 100 cases consisting of 21FA and 79 PTs were freshly frozen tissues. Details of the samples used in this study are given in table 1 below. 69 of these were normal tissues. An additional 5 FFPE (formalin fixed paraffin embedded) tablets were included in the study, including concurrent (n-3) and longitudinal (n-2) cases, and were included later in the study.

TABLE 1 clinical characteristics of patients with fibroepithelial tumors

Both tumor and whole blood were obtained from patients with informed consent to surgical resection of fibroepithelial tumors. Genomic DNA (gdna) from fresh frozen tissue was extracted and purified using Qiagen blood and cell culture DNA kits. Genomic DNA yield and quality Picogreen was used^TMFluorescence analysis and visual inspection of agarose gel electrophoresis images. For FFPE samples from concurrent or longitudinal fibroepithelial tumors, the qiagen nffpe tissue kit was used.

Example 2

Whole exome sequencing was performed in leaf tumors of 22 matched tumor-normal pairs. Using recommended settings, Covariist (TM) is used^S2The (Covaris) system segments whole genomic DNA. Sequencing linker ligation was performed using the TruSeq paired-end genomic DNA kit (Illumina). To enrich for coding sequences, we used the TruSeq exome sequencing kit (Illumina) according to the manufacturer's recommended protocol. The enriched exome pool was then sequenced on the IlluminaHiSeq 2000 instrument to generate 76bp paired-end reads. As in the previous work⁴⁶Bioinformatic analysis, including sequence alignment, variation calling, and identification of candidate somatic variants, is performed. Variants were filtered, leaving only those covered by at least 15 reads and having at least three variant reads. Furthermore, those with Variant Allele Frequencies (VAFs) below 5% were excluded. Simple repeat regions where indels overlap are discarded. In IGV genome browser⁴⁷All remaining candidate variants were visually inspected to exclude possible germline mutations and sequencing artifacts. Synonymous mutations identified in exome sequencing are included in table 2 below.

TABLE 2 List of synonymous mutations identified from Whole exome sequencing of 22 fronds

PCR amplification was performed using Platinum Taq polymerase (Life Technologies). The PCR program included 1 cycle at 95 ℃ for 10 minutes, 35 cycles at 95 ℃ for 30 seconds, 30 seconds at 58 ℃,1 minute at 72 ℃ and 1 cycle at 10 minutes at 72 ℃. BigDye Terminator v.3.1 kit (Applied Biosystems) was used for the bidirectional sequencing of the generated PCR amplicons and the products were fractionated using ABI PRISM 3730 genetic Analyzer (Applied Biosystems). The sequencing record was aligned to the reference sequence using Lasergene 10.1(DNASTAR) and visually analyzed. The present disclosure selects 60 putative somatic mutations for Sanger validation (including tumor and normal samples) that include mutations in frequently mutated genes, cancer-associated genes, and randomly selected genes. Of these 54 mutations were successfully verified, 4 were found to be false positives, and 2 failed sequencing, indicating a true positive rate of 90%. Validated mutations are highlighted with an asterisk in table 3.

TABLE 3 list of candidate somatic mutations identified from Whole exome sequencing of 22 leaf tumors

Note that: frequent genes are in bold and verified by Sanger sequencing

Mutations verified by Sanger sequencing

The invention performed whole exome sequencing of 22 matched tumor-normal paired PTs, including 10 benign, 8 borderlines and 4 malignant PTs (table)1). Sequencing of PT exome and paired normal samples, the average coverage was 66-fold, with an average of 78% of the bases covered by at least 20 reads (table 2). The inventors of the present disclosure identified 333 non-synonymous or splice site somatic mutations in total among 310 genes. Sanger sequencing of frequent mutations (mutations in at least two cases) and single mutations of interest yielded a validation rate of 90% (table 3). Despite the comparison with previous FA studies performed by the present inventors (66X vs 124X), the median number of non-silent somatic mutations/cases in PT was higher than FA (13vs 5, p)<0.001) as shown in fig. 3A. Relatively low mutation counts in PT with other interstitial tumors such as sarcomas and leiomyomas^24-26The mutation counts of (c) were comparable. The average nonsynonymous mutation rate per megabase in PT was 0.192(NS/S ratio 3.2, fig. 3B), the main mutation feature was C at NpCpG site>T substitution, as shown in FIG. 3C.

Example 3

A set of 50 selected genes (including the frequent mutant genes in the PT discovery cohort, FA) was designed using the SureDesign tool (Agilent)²Mutated genes and genes associated with breast cancer²⁰). Sequencing libraries were prepared from 68 paired tumor-normal samples and DNA extracted from 32 tumors using the SureSelect XT2 targeted enrichment system against the Illumina multiplex sequencing platform (Illumina) according to the manufacturer's instructions. The enriched target library was then sequenced on the Illumina HiSeq 2000 sequencing platform to generate 76bp paired-end reads. For paired tumor-normal samples, the analysis was performed as described in the exome sequencing analysis section. Furthermore, Strelka was used due to higher sequencing coverage (average coverage of samples of the target area is at least 228X)⁴⁸(Illumina) somatic variant caller to identify low allele frequency variants (at least 3%). All candidate variants were visually inspected in IGVs to confirm that they are likely somatic. For patients with tumor samples only, only gene variants with frequent mutations in paired tumor-normal samples were considered. The present disclosure also uses a more stringent variant allele frequency cutoff for SNV (at least 5%) and indels (at least 10%). Discarding simple repeat regions where variants overlap, and dbSNP⁴⁹(version 137) stripVariants of interest. Variants were also filtered through an internal database consisting of germline variations identified by inclusion of approximately 512 east asian exomes to further remove possible germline polymorphisms. These variants were also visually inspected by IGV to exclude possible sequencing artifacts.

To validate PT exome sequencing data, the inventors of the present disclosure performed targeted depth sequencing in a diseased population of 100 fibroepithelial tumors (21 FA, 34 benign, 35 borderlines and 10 malignant PTs as shown in table 1), including 22 cases from the test group. The present invention sequenced a total of 50 genes, including frequent and single mutations of the gene of interest in our test panel, as well as previously reported in the FAs²And BCs^20-22,27Of (a) a mutated gene. The average coverage of the target gene was 524X (228X minimum). The present disclosure recognizes that a relatively low mean depth of coverage (66X) in exome sequencing of PT is a limitation of the present study and may lead to deficiencies in sequence variants. This is supported by further observations that 11 of the 59 mutations identified by targeted sequencing (cut-off of 20% variant frequency) were missed by exome sequencing, resulting in a false negative rate of 18.6%, probably due to low coverage. Furthermore, due to the rarity of PT and the relatively small detection set, mutations that occur infrequently in patients may be missed by the present study, as these mutations will be excluded from the target sequencing set.

Example 4

Using OncoCNV²⁸Copy number estimates for each gene in the targeted sequencing study were obtained. In short, the coverage depth information for each target area is generated from the BAM file and normalized to the normal sample pool and GC content. The probe level copy number estimates are then summed to obtain an estimate of the gene level copy number. Genes with copy number estimates less than 1.5 or more than 3 are considered to have copy number increases or losses. We used Control-FREEC²⁹Copy Number Alterations (CNAs) in our exome sequencing cohort were identified as well as regions with LOH.

To investigate the potential function of point mutations, we performed SIFT separately⁵⁰，Polyphen2⁵¹，CHASM⁵²And PROVEAN⁵³And (4) waiting for mutation prediction algorithm. Functional mutations are shown in table 4 as being disrupted or possibly disrupted and deleterious. Cancer specific mutations are indicated for the driver or passenger. Neutral mutations appear to be tolerated or benign.

TABLE 4 somatic mutations in 100 fibroepithelial tumors detected by targeted sequencing

Note that: the frequency gene is bold

Unpaired samples of normal tissue

Using COSMIC v69 version

Value <0.05 (driver) >0.05 (passenger) of CHASM p

# was detected in exome sequencing and the cDNA + gDNA was verified by Sanger sequencing. Variant reads that are present in targeted sequencing but are not considered due to strand bias.

Filtered out as a result of allele frequencies > 45% and < 55% in tumor samples, but retained as a result of the mutation having been identified as a somatic mutation in other paired samples (and also listed in COSMIC)

From the experiments performed as described above, the present disclosure identified 20 frequent mutant genes in fibroepithelial tumors as summarized in fig. 1 a. Additionally, the present disclosure uses an OncOCNV²⁸Detecting a copy number alteration of the target gene. The results obtained are shown in FIG. 1A, FIG. 3D and Table 6, confirming the use of Control-FREEC²⁹The loss of heterozygosity (LOH) pattern of the mutation in the sample with exome sequencing data.

TABLE 5.100 copy number alterations of 50 target genes in fibroepithelial tumors

Sample numbering

Gene symbol

Transcript numbering

Chromosome

Initiation of

Terminate

Number of copies

P-value

Q-value

Sample 1076

EGFR

CCDS5514.1

chr7

55086911

55273341

18

1.56E-15

3.27E-14

Sample 1056

EGFR

CCDS5514.1

chr7

55086911

55273341

11.5

2.23E-15

4.24E-14

Sample 1076

NF1

CCDS42292.1

chr17

29422297

29701221

1

9.78E-34

2.25E-32

Sample 1078

NF1

CCDS42292.1

chr17

29422297

29592421

1

1.88E-18

4.52E-17

Sample 1078

NF1

CCDS42292.1

chr17

29652813

29665892

0

1.89E-08

4.16E-07

Sample 1074

PTEN

CCDS31238.1

chr10

89624175

89725256

1

2.84E-05

5.10E-04

Sample 1011

SETD2

CCDS2749.2

chr3

47058543

47205468

1

6.35E-17

1.27E-15

Sample 1078

TP53

CCDS45606.1

chr17

7569531

7579965

1

4.82E-07

9.64E-06

Note that: genes with copy number estimates less than 1.5 or more than 10 are considered to have a copy number loss or increase. For copy number alterations, only the loss of tumor suppressor genes and the amplification of oncogenes are included. The P-value and q-value are generated by the OncOCNV algorithm.

Comparison of frequent mutations in fibroepithelial tumors revealed different patterns of mutations and pathways associated with different stages in the mammary fibroepithelial tumor profile, as shown in fig. 1A and 1B. First, mutations in MED12 and RARA (nuclear retinoic acid receptor α) are frequently found at all stages of fibroepithelial tumors, occurring in 73% and 32% of tumors, respectively. It was confirmed that in early studies, the MED12 exon 2 mutation in fibroepithelial tumors was identical to that reported in uterine leiomyomas, but was identical to that of prostate and adrenocortical carcinomas^30,31The pattern and position of the MED12 mutation found in (a) were different. Notably, RARA mutations were also observed in more than one-third of the fibroepithelial tumors by the present disclosure (fig. 2B). Prior to this study, somatic missense mutations in PML-RARA were only in drug-resistant Acute Promyelocytic Leukemia (APL)³²Reported, or low frequency: (<5%) are scattered in other solid tumors. Fibroepithelial RARA mutations are highly aggregated within the nuclear hormone receptor Ligand Binding Domain (LBD), including missense mutations and in-frame deletions, together with those mutations that may affect the interaction between RARA and other binding partners-aThus, the method can be used for the treatment of the tumor. Interestingly, both MED12 and RARA are involved in estrogen signaling and estrogen-regulated transcription^33,34Relatedly, the co-incidence of MED12 and RARA mutations was higher than expected at random (replacement test p-value 0.0046,100000 trials). These results suggest that PTs and FAs may share a common cause, with MED12 and RARA mutations being early events that may interact or cooperate to cause hormonal dysregulation of this tumor type.

Second, the present disclosure also observed the presence of new mutations in PT (benign, borderline and malignant) FLNA, SETD2, MLL2, BCOR and MAP3K1, which are rarely present in FA (fig. 1A, exact assay values for Fisher compared to FA ═ 1E-04). This finding suggests that PT tumorigenesis may involve these additional mutated genes. Among them, FLNA is particularly novel. The X chromosome gene FLNA encodes filamin A, an F-actin cross-linked protein, which passes through integrin receptors³⁵Interactions, acting as scaffold proteins, regulate signaling events involved in cell motility and invasion. FLNA mutations in fibroepithelial tumors (28%, 28/100) were observed particularly in the F-actin binding region, especially in the immunoglobulin (Ig) -like repeat 9-15 domain (80%, 24/30)³⁶In (1). In contrast, as shown in FIGS. 5A and 5B, it was reported that FLNA mutations of BC affect mainly other Ig-like repeat domains than the F-actin binding region. These results indicate that the functional role of FLNA in PT may be different from that in BC. Using cDNA Sanger sequencing, the present disclosure confirmed expression of FLNA mutant transcripts, indicating that FLNA mutations may occur on the active X chromosome.

In addition to FLNA, more than one-third (35%) of the PTs also have mutations in at least one of two chromatin modifying enzymes; SETD2 (21%) and MLL2 (12%) (Fisher test p-value compared to FA ═ 0.0058, see further fig. 1A). The SETD2 and MLL2 mutations showed typical tumor suppressor loss-of-function mutation patterns, including inactivating mutations and deletions^37,38. Both SETD2 and MLL2 are histone methyltransferases that mediate epigenetic regulation, and inactivation of these genes may lead to aberrant transcriptional regulation through chromatin modification.

Again, the boundary and malignant PTs are also in contrast to benign PTsNF1, RB1, TP53, PIK3CA, ERBB4, and EGFR show additional mutations, which are cancer-driving genes known to have transforming ability. Copy Number Alterations (CNAs) of these genes are also found in borderline/malignant PT. These findings are consistent with previous studies, with TP53 and RB1 being found in malignant PTs^{39 -41}Is unregulated. Interestingly, while the variation frequency of individual cancer-associated genes was low, 29% (13/45) of border/malignant PTs showed possible driver variations (defined as frequent mutations and loss of function mutations (nonsense/frameshift) of cosinc or high levels of CNAs) in at least one of the cancer-associated genes. In contrast, 55 FAs and benign PT (0/55, 0%) did not have a genetic variation in these genes (Fisher's exact test, p-value 1.02E-05). These results indicate that these cancer-associated genes may be involved in high-grade PT subtypes. Notably, both tumors apparently contained a true PIK3CA activating mutation (H1047R/L), with both tumors having high levels of EGFR amplification, as shown in fig. 6A and 6B. Taken together, these findings provide important insight into the genetic basis of tumorigenesis of various subtypes of fibroepithelial tumors.

Example 5

For example, FA, PT are fibroepithelial tumors, including mixtures of epithelial and stromal compartments. To determine the location and distribution of PT-associated mutations identified in this study, the present disclosure further performed Laser Capture Microdissection (LCM) on the 6 PTs found in the series. Isolated epithelial and stromal components were subjected to mutation analysis in MED12, RARA, FLNA, SETD2, BRCA1 and PIK3CA, respectively, the latter two genes being frequently mutated in BC but less in PT (see paragraph below). Briefly, fresh frozen tissues of 6 leaf tumors were embedded in Optimal Cutting Temperature (OCT) compound (Tissue-Tek, Sakura Finetek) and sectioned (8 μm thick) in a Microtome-cryostat (Leica) mounted in Microtome-cryostat (Leica)

PEN membrane slides (Life Technologies) were then stored at-80 ℃ until needed. The slides were dehydrated and used according to the manufacturer's recommendations

And (4) staining by Histogene. The stained slides were loaded into a laser capture microscope stage (ArcturusxT)^TMLaser Capture Microdissection (LCM) system). Then the Capsule is processed^TMA Macro LCM cap (cap) (Life Technologies) is automatically placed over a selected area of tissue. Once the software-highlighted cell of interest is verified by the user, the machine will automatically dissect the highlighted cell using a near-infrared laser or ultraviolet pulse, transferring it to Capsule^TMOn a Macro LCM cap. DNA was extracted directly from the LCM cap using Qiagen FFPE DNA tissue kit according to the manufacturer's protocol and the following changes were made. Each sample was covered with lysis buffer (ATL)&Proteinase K) was incubated in a 500. mu.l microcentrifuge for 5 hours at 60 ℃ and enzyme inactivation was carried out for 10 minutes at 90 ℃. The eluted DNA was used directly in PCR and

and (5) sequencing.

The present disclosure found that all PT-associated mutations were present in stromal cells, but not in epithelial cells. These observations are consistent with previous studies in FAs in which the MED12 mutation was only in the tumor stroma²Detected, indicates that FAs and PTs are likely to originate from stromal cells rather than epithelial cells, despite their biphasic epithelial-stromal morphological appearance. However, it should be noted that the present results do not exclude the possibility that there are also genetic variations between epithelial cells of fibroepithelial tumors. LOH in chr1q was observed in 21% of fibroepithelial tumors in this disclosure by using OncoCNV analysis, consistent with previous studies⁴². In addition, at PT⁴³Epithelial variation was frequently observed and, as shown in table 6, histopathological evaluation indicated that 49% of PT (32/65, with appreciable epithelial compartments) showed moderate to fully developed ductal hyperplasia, an epithelial phenotype⁴. Thus, the development of mammary fibroepithelial tumors may involve a complex interaction between the epithelial and stromal compartments of these tumors, requiring further investigation.

TABLE 6 epithelial hyperplasia in phyllodes tumors

Comparison between the mutation spectrum and frequency in fibroepithelial tumors compared to BC showed significant differences as summarized in figure 7. MED12, RARA, FLNA, SETD2, and MLL2 are commonly mutated in FA and PT but not in BCs, whereas TP53, PIK3CA, GATA3, and CDH1 mutations are rare in fibroepithelial tumors but ubiquitous in BCs. These mutation patterns, as well as the stromal localization of the fibroepithelial-associated driver mutations, suggest that there is a clear molecular pathogenesis between BC and mammary fibroepithelial tumors, supporting the current guidelines that these two tumor types are considered to be distinct disease entities and should be managed differently.

Example 6

The full-length RARA cDNA was cloned into pcDNA3.1 using a3 Xflag tag. Patient-derived mutations were introduced using the QuikChange II XL site-directed mutagenesis kit (Agilent), as described in the manufacturer's instructions. The transcriptional activity of wild-type and mutant RARA was assessed by luciferase assay using the RARE (retinoic acid responsive element) Cignal reporter assay kit (Qiagen). HEK293 cells were transiently transfected with RARE reporter construct and Renilla (Renilla) luciferase construct from the kit, as well as wild type or mutant RARA plasmids as described above. Transfected cells were then incubated with the indicated concentration of RA for 24 hours. The luciferase assay was performed using the dual luciferase reporter assay system (Promega) according to the manufacturer's instructions. Results were normalized to co-expressed renilla.

For mammalian two-hybrid assays, the RARA ligand binding domain was cloned into the pACT vector (Promega) to generate a bait plasmid, and the cDNA sequence encoding the NCoR1 protein, the corrr 1 peptide region (THRLITLADHICQIITQDFARNQV), was inserted into pBIND, thereby generating a prey plasmid. Mammalian two-hybrid screens were performed using the CheckMate mammalian two-hybrid system (Promega) according to the manufacturer's protocol. Briefly, transfected HEK293T cells were treated with the indicated concentration of RA for 24 hours and luciferase activity was measured. Results were normalized to co-expressed renilla.

As shown in figure 4A, this study followed an investigation of its functional importance in view of the specific high frequency of RARA mutations in fibroepithelial tumors. Previous studies have determined that RARA is a transcription factor that can interact with co-repressors and co-activators to regulate gene expression. The results shown in figure 4B show that there was no significant difference in RARA expression levels between fibroepithelial tumors carrying wild-type and mutated RARA genes. However, by computational analysis, almost all RARA missense mutations were classified as either disrupted or deleterious, indicating that they are of biological significance. To examine the effect of RARA mutations on RARA-mediated transcriptional activation, the present disclosure transfected HEK293 cells with RARE (retinoic acid responsive element) reporter constructs and cDNA vectors expressing wild-type RARA or RARA mutations (F286del, S287L, N299H, and R394Q). RARA transcriptional activity was then measured before and after Retinoic Acid (RA) stimulation. In cells expressing wild-type RARA, stimulation with RA caused a significant increase in RARE-related transcription. In contrast, cells expressing the RARA mutant form showed a marked reduction in transcriptional activity even after RA stimulation, as shown in figure 4C. The present disclosure hypothesizes that the attenuation of RARA mutant transcriptional activity may result, at least in part, from these mutations that result in enhanced RARA binding to the co-repressor protein. To test this possibility, the present disclosure used a mammalian two-hybrid assay to probe wild-type and mutant RARA proteins for co-suppression with NcoR1 (known RARA interactors)⁴⁴The interaction of (a). The RARA mutant showed higher binding signals to NCoR1 both before and after RA stimulation compared to wild-type RARA, as shown in figure 4D, indicating that the mutant RARA was a more potent co-suppressor recruiter. Taken together, these results indicate that in mammary fibroepithelial tumors, aggregating mutations in RARA may promote RARA interaction with cosuppressing factors, thereby altering RARA target gene transcription.

Example 7

To confirm the expression of mutant FLNA, the present study also sequenced cDNA of three FLNA mutant samples with available fresh frozen tissue. One hundred RNAs were converted to cDNAs using SuperScript III First-Strand Synthesis SuperMix from Invitrogen according to the manufacturer's recommended protocol. PCR was performed according to the primers listed in Table 7. As described above, to sequence genomic DNASanger, PCR amplification, sequencing and fractionation were performed.

TABLE 7 primers for FLNA cDNA sequencing

Primer and method for producing the same	Forward sequence 5' ->3'	Reverse sequence 5->3'
			FLNA-A1191+Y1235	CTCTTCGCTGACACCCACATCC	TCCACACTGAACTCAGTGGTGG
FLNA-G1578	CCCAGACCGTCAATTATGTGCC	GGGATCTCGTCACCACCGTACT

Finally, the present disclosure investigated whether FAs progressed to malignant PT in a linear fashion, as in previous studies^6-10The method as set forth in (1). Pairs of concurrent FA and PT-like regions isolated from the same patient (N-3) were experimentally determined using the same 50 gene target set. The present disclosure also analyzed paired longitudinal tumors from two patients with initial diagnosis of FAs, but subsequent PT-like relapse. It has been found that even in the same patient, higher order PTs have more mutations than the paired FA regions, particularly in the cancer-associated genes shown in table 8 and fig. 10B. Of these patients, two patients,one of them is concurrent and one is longitudinal, with the paired FAs and PTs sharing a common mutation, consistent with linear progression. However, the third patient (longitudinal) showed FA and PT lesions with different MED12 mutations, supporting multiple focal origins. The remaining two concurrent cases showed no mutations in FA and were therefore considered to be non-informative. Overall, these observations suggest that breast fibroepithelial tumor progression may not always follow a strict linear progression model, but may also be caused by a multifocal pattern of independent lesions in the same breast.

The genomic blueprints of mammary fibroepithelial tumors described in this disclosure may have significant clinical significance. As previously mentioned, diagnosis and histopathological classification of PT often presents a challenge to pathologists. The present disclosure provides a basis for the classification of breast fibroepithelial tumor-based genomics, which can increase diagnostic accuracy when used in conjunction with histopathological criteria. For example, based on the sequencing data obtained, sample 004 previously histologically classified as benign FA was found to have R1B truncation and EGFR activating mutations, consistent with borderline/malignant PT features, in addition to MED12, RARA and FLNA mutations (see fig. 9). The case was then reevaluated by 2 breast pathology experts and confirmed as critical PT. This situation supports the notion that sequencing mutation analysis may improve the ability to classify fibroepithelial tumors, particularly tumors associated with malignant states. In addition to diagnostics, the invention also discloses candidate therapeutic targets for PT. In particular, the typical activating mutations in PIK3CA and the high level amplification of EGFR were only found in higher-grade PT patients, indicating potential therapeutic opportunities for EGFR-and PI 3K-targeted therapy. This is particularly important for aggressive malignant PT, for which there is currently no effective treatment option other than surgery. Also of interest are mutations affecting MED12 and RARA, which are highly frequent in fibroepithelial tumors and may affect nuclear hormone receptor signaling^34,45. The experimental data determine the effect of missense RARA missense mutation in solid tumors for the first time, further emphasizing the importance of RARA in fibroepithelial tumors. Thus, these genes may represent potential therapeutic targets。

Although the disclosed methods and kits have been described in its preferred form with a certain degree of particularity, it is understood that the preferred form of the disclosure has been made only by way of example and that numerous changes in the details of construction and the combination and arrangement of parts may be resorted to without departing from the scope of the disclosure.

Reference to the literature

1.Lakhani,S.,Ellis,I.,Schnitt,S.,Tan,P.&Van de Vijver,M.World Health Organisation Classification of tumors of the breast,vol4.,142-147(International Agency for Research on Cancer,Lyon,2012).

2.Lim,W.K.et al.Exome sequencing identifies highly recurrent MED12somatic mutations in breast fibroadenoma.Nat Genet46,877-80(2014).

3.Coriaty Nelson,Z.,Ray,R.M.,Gao,D.L.&Thomas,D.B.Risk factors for fibroadenoma in a cohort of female textile workers in Shanghai,China.Am J Epidemiol156,599-605(2002).

4.Tan,P.H.et al.Phyllodes tumors of the breast:the role of pathologic parameters.Am J Clin Pathol123,529-40(2005).

5.Krishnamurthy,S.,Ashfaq,R.,Shin,H.J.&Sneige,N.Distinction of phyllodes tumor from fibroadenoma:a reappraisal of an old problem.Cancer90,342-9(2000).

6.Hodges,K.B.et al.Evidence for transformation of fibroadenoma of the breast to malignant phyllodes tumor.Appl Immunohistochem Mol Morphol17,345-50(2009).

7.Kuijper,A.et al.Analysis of the progression of fibroepithelial tumours of the breast by PCR-based clonality assay.J Pathol197,575-81(2002).

8.Noguchi,S.et al.Progression of fibroadenoma to phyllodes tumor demonstrated by clonal analysis.Cancer76,1779-85(1995).

9.Kasami,M.et al.Monoclonality in fibroadenomas with complex histology and phyllodal features.Breast Cancer Res Treat50,185-91(1998).

10.Abe,M.et al.Malignant transformation of breast fibroadenoma to malignant phyllodes tumor:long-term outcome of 36malignant phyllodes tumors.Breast Cancer18,268-72(2011).

11.Cani,A.K.et al.Next-Gen Sequencing Exposes Frequent MED12Mutations and Actionable Therapeutic Targets in Phyllodes Tumors.Mol Cancer Res13,613-9(2015).

12.Yoshida,M.et al.Frequent MED12mutations in phyllodes tumours of the breast.Br J Cancer112,1703-8(2015).

13.Piscuoglio,S.et al.MED12somatic mutations in fibroadenomas and phyllodes tumours of the breast.Histopathology(2015).

14.Nagasawa,S.et al.MED12exon 2mutations in phyllodes tumors of the breast.Cancer Med (2015).

15.Jones,A.M.et al.mRNA expression profiling of phyllodes tumours of the breast:identification of genes important in the development of borderline and malignant phyllodes tumours.J Pathol216,408-17(2008).

16.Ang,M.K.et al.Molecular classification of breast phyllodes tumors:validation of the histologic grading scheme and insights into malignant progression.Breast Cancer Res Treat129,319-29(2011).

17.Huang,K.T.et al.DNA methylation profiling of phyllodes and fibroadenoma tumours of the breast.Breast Cancer Res Treat124,555-65(2010).

18.Tan,W.J.et al.Novel genetic aberrations in breast phyllodes tumours:comparison between prognostically distinct groups.Breast Cancer Res Treat145,635-45(2014).

19.Jones,A.M.et al.A comprehensive genetic profile of phyllodes tumours of the breast detects important mutations,intra-tumoral genetic heterogeneity and new genetic changes on recurrence.J Pathol214,533-44(2008).

20.Comprehensive molecular portraits of human breast tumours.Nature490,61-70(2012).

21.Banerji,S.et al.Sequence analysis of mutations and translocations across breast cancer subtypes.Nature486,405-9(2012).

22.Curtis,C.et al.The genomic and transcriptomic architecture of 2,000breast tumours reveals novel subgroups.Nature486,346-52(2012).

23.Ellis,M.J.et al.Whole-genome analysis informs breast cancer response to aromatase inhibition.Nature486,353-60(2012).

24.Brohl,A.S.et al.The genomic landscape of the Ewing Sarcoma family of tumors reveals recurrent STAG2 mutation.PLoS Genet10,e1004475(2014).

25.Lawrence,M.S.et al.Mutational heterogeneity in cancer and the search for new cancer-associated genes.Nature499,214-8(2013).

26.Makinen,N.,Vahteristo,P.,Butzow,R.,Sjoberg,J.&Aaltonen,L.A.Exomic landscape of MED12 mutation-negative and-positive uterine leiomyomas.Int J Cancer134,1008-12(2014).

27.Stephens,P.J.et al.The landscape of cancer genes and mutational processes in breast cancer.Nature486,400-4(2012).

28.Boeva,V.et al.Multi-factor data normalization enables the detection of copy number aberrations in amplicon sequencing data.Bioinformatics30,3443-50(2014).

29.Boeva,V.et al.Control-FREEC:a tool for assessing copy number and allelic content using next-generation sequencing data.Bioinformatics28,423-5(2012).

30.Barbieri,C.E.et al.Exome sequencing identifies recurrent SPOP,FOXA1 and MED12mutations in prostate cancer.Nat Genet44,685-9(2012).

31.Assie,G.et al.Integrated genomic characterization of adrenocortical carcinoma.Nat Genet46,607-12(2014).

32.Zhu,H.H.,Qin,Y.Z.&Huang,X.J.Resistance to arsenic therapy in acute promyelocytic leukemia.N Engl J Med370,1864-6(2014).

33.Kang,Y.K.,Guermah,M.,Yuan,C.X.&Roeder,R.G.The TRAP/Mediator coactivator complex interacts directly with estrogen receptors alpha and beta through the TRAP220subunit and directly enhances estrogen receptor function in vitro.Proc Natl Acad Sci USA99,2642-7(2002).

34.Ross-Innes,C.S.et al.Cooperative interaction between retinoic acid receptor-alpha and estrogen receptor in breast cancer.Genes Dev24,171-82(2010).

35.Savoy,R.M.&Ghosh,P.M.The dual role of filamin A in cancer:can't live with(too much of)it,can't live without it.Endocr Relat Cancer20,R341-56(2013).

36.Nakamura,F.,Osborn,T.M.,Hartemink,C.A.,Hartwig,J.H.&Stossel,T.P.Structural basis of filamin A functions.J Cell Biol179,1011-25(2007).

37.Zhu,X.et al.Identification of functional cooperative mutations of SETD2 in human acute leukemia.Nat Genet46,287-93(2014).

38.Pasqualucci,L.et al.Analysis of the coding genome of diffuse large B-cell lymphoma.Nat Genet43,830-7(2011).

39.Cimino-Mathews,A.et al.A subset of malignant phyllodes tumors harbors alterations in the Rb/p16 pathway.Hum Pathol44,2494-500(2013).

40.Feakins,R.M.,Mulcahy,H.E.,Nickols,C.D.&Wells,C.A.p53 expression in phyllodes tumours is associated with histological features of malignancy but does not predict outcome.Histopathology35,162-9(1999).

41.Millar,E.K.et al.Malignant phyllodes tumours of the breast display increased stromal p53protein expression.Histopathology34,491-6(1999).

42.Sawyer,E.J.et al.Molecular analysis of phyllodes tumors reveals distinct changes in the epithelial and stromal components.Am J Pathol156,1093-8(2000).

43.Jara-Lazaro,A.R.&Tan,P.H.Molecular pathogenesis of progression and recurrence in breast phyllodes tumors.Am J Transl Res1,23-34(2009).

44.Altucci,L.&Gronemeyer,H.The promise of retinoids to fight against cancer.Nat Rev Cancer1,181-93(2001).

45.Markowski,D.N.et al.MED12 mutations in uterine fibroids--their relationship to cytogenetic subgroups.Int J Cancer131,1528-36(2012).

46.Chan-On,W.et al.Exome sequencing identifies distinct mutational patterns in liver fluke-related and non-infection-related bile duct cancers.Nat Genet45,1474-8(2013).

47.Thorvaldsdottir,H.,Robinson,J.T.&Mesirov,J.P.Integrative Genomics Viewer(IGV):high-performance genomics data visualization and exploration.Brief Bioinform14,178-92(2013).

48.Saunders,C.T.et al.Strelka:accurate somatic small-variant calling from sequenced tumor-normal sample pairs.Bioinformatics28,1811-7(2012).

49.Sherry,S.T.et al.dbSNP:the NCBI database of genetic variation.Nucleic Acids Res29,308-11(2001).

50.Ng,P.C.&Henikoff,S.SIFT:Predicting amino acid changes that affect protein function.Nucleic Acids Res31,3812-4(2003).

51.Reva,B.,Antipin,Y.&Sander,C.Predicting the functional impact of protein mutations:application to cancer genomics.Nucleic Acids Res39,e118(2011).

52.Carter,H.et al.Cancer-specific high-throughput annotation of somatic mutations:computational prediction of driver missense mutations.Cancer Res69,6660-7(2009).

53.Choi,Y.&Chan,A.P.PROVEAN web server:a tool to predict the functional effect of amino acid substitutions and indels.Bioinformatics(2015).

Claims (11)

1. A kit for identifying a tumor type in breast tissue of a subject, comprising:

at least one platform capable of performing one or more nucleic acid-based assays to identify a mutation present in breast tissue obtained from a subject according to a first test module and a second test module, each of the first and second test modules being associated with detection of at least one predetermined mutation in one or more genes and each configured to provide a positive result corresponding to detection of at least one predetermined mutation in the tissue or a negative result corresponding to absence of a detectable predetermined mutation in the sample, the first test module being associated with detection of a mutation in the MED12 gene and the second test module being associated with detection of a mutation in the FLNA gene and a mutation in the SETD2 gene;

wherein the test module is configured to emit a detectable or visible signal corresponding to any positive result;

wherein the type of tumor is considered as a fibroadenoma when the results of the first test module and the second test module are positive and negative, respectively, and the type of tumor is considered as a phylloid tumor when the results of the first test module and the second test module are positive, respectively;

wherein the FLNA gene mutation corresponds to p.A1191T, p.S1199L, p.P1244S, p.1687-1688TV > M and/or p.S1186W found in the translated polypeptide.

2. The kit of claim 1, wherein the at least one platform further comprises a third test module that is associated with detection of NF1 gene mutations, RB1 gene mutations, and/or PIK3CA gene mutations.

3. The kit of claim 1, wherein the first test module is further associated with detection of RARA gene mutations.

4. The kit of claim 1, wherein the first test module is further associated with detection of a TERT gene mutation in the subject.

5. The kit of claim 2, wherein the type of tumor is considered a malignant phylloid tumor when the results of the first test module, the second test module, and the third test module are all positive.

6. The kit of claim 1, wherein the MED12 gene mutation is a splice site mutation located at position-8 of exon 2 of the MED12 gene, a missense mutation located at codon 44 of the MED12 gene cDNA or a missense mutation located at codon 36 of the MED12 gene cDNA.

7. The kit according to claim 3, wherein the RARA gene mutation corresponds to p.F286del, p.F287L, p.N299H, p.R394Q, p.L409del and/or p.G289R found in a translated polypeptide.

8. The kit of claim 1, wherein the second test module is further associated with detection of a mutation in the MLL2 gene in the subject.

9. The kit of claim 1, wherein the SETD2 gene mutation corresponds to p.R1674-1675EA > D, p.K1587fs, p.Q1545 x, p.Y1605fs and/or p.F1651fs found in translated polypeptide.

10. The kit of claim 4, wherein the TERT gene mutation corresponds to a missense mutation at-124 and/or-146 of the TERT gene promoter region.

11. The kit according to claim 8, wherein the MLL2 gene mutation corresponds to p.V5482fs, p.Q1139, p.G2668fs, p.Q3814 and/or p.L3457fs found in the polypeptide translated therefrom.

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